1. Technical Field
The present invention relates generally to character recognition systems, and relates more particularly to an optical character recognition system for reading E13B character data utilizing a MICR-based algorithm.
2. Related Art
Various applications require the automated processing of materials having printed characters. One common application involves the processing of checks by, e.g., a bank, a cashier at a retail store, etc. A popular technology for processing checks reads a set of special characters at the bottom of the check, which are called Magnetic Ink Character Recognition (MICR) characters. These characters are generally printed in a font referred to as E13B, and contain information regarding account number, routing numbers, etc. To implement such a system, the characters are printed in a magnetic ink so that the characters can be read magnetically. Accordingly, MICR technology is limited to applications that utilize magnetic ink (e.g., checks printed on home computers that do not use magnetic ink cannot be read by MICR systems).
Once the characters are magnetically read, well established MICR-based algorithms are implemented to identify each E13B character. MICR-based systems and algorithms are described, for example, in U.S. Pat. No. 6,243,504 B1, “Integrated Magnetic Ink Character Recognition System and Method Therefor,” issued on Jun. 5, 2001 to Kruppa, and U.S. Pat. No. 5,026,974, Method for Recognizing the Leading Edge of a Character in E13B Font,” issued on Jun. 25, 1991 to Franlin et al., which are hereby incorporated by reference.
While most MICR systems utilize a single gap read head that provides marginal read-rate performance, IBM Corporation's 3890 system utilizes a multigap read head, along with a multigap MICR algorithm, to provide higher performance. Although multigap MICR systems generally provide superior read rates (i.e., low error rate), the systems are relatively expensive since they require multigap magnetic read heads.
A potential solution to the aforementioned problems is to use multiple lower cost recognition engines that perform independent analysis of the characters being read (referred to herein as “a multi-voting character recognition system”). A relatively inexpensive recognition engine may be implemented using known OCR (optical character reader) technology. OCR technology reads characters electro-optically and therefore does not require magnetic ink.
However, in order to provide a high level of accuracy, each character recognition engine must implement a unique feature set or feature vector for identifying characters. Unfortunately, the costs of developing, testing, and implementing new feature sets may be significant. Accordingly, a need exists for independent feature sets for recognizing characters in a multi-voting recognition system that can utilize low cost technologies, such as OCR.